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English Information

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Authors
# Name
1 Bárbara Mendes(barbaramit@ufmg.br)
2 Camila Braz(camilabraz@ufmg.br)
3 Lucas Costa(lucas-lage@ufmg.br)
4 Gabriel Oliveira(gabrielpoliveira@dcc.ufmg.br)
5 Henrique Hott(henriquehott@dcc.ufmg.br)
6 Mariana Silva(mariana.santos@dcc.ufmg.br)
7 Gisele Pappa(glpappa@dcc.ufmg.br)

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Reference
# Reference
1 Attard, J., Orlandi, F., Scerri, S., and Auer, S. (2015). A systematic review of open government data initiatives. Government information quarterly, 32(4):399–418.
2 Costa, L. L. et al. (2022). Alertas de fraude em licitações: Uma abordagem baseada em redes sociais. In BraSNAM, pages 37–48, Porto Alegre, Brasil. SBC.
3 Cuturi, M. and Blondel, M. (2017). Soft-dtw: a differentiable loss function for timeseries. In ICML, pages 894–903. PMLR.
4 Lima, M. et al. (2020). Inferring about fraudulent collusion risk on Brazilian public works contracts in official texts using a Bi-LSTM approach. In EMNLP, pages 1580–1588, Online. Association for Computational Linguistics.
5 Lyra, M. S. et al. (2021). Characterization of the firm–firm public procurement co-bidding network from the State of Ceará (Brazil) municipalities. Appl. Network Sci., 6(1):1–10.
6 Oliveira, E. F. and Silveira, M. S. (2018). Open Government Data in Brazil a Systematic Review of Its Uses and Issues. In dg.o, dg.o ’18, New York, NY, USA. ACM.
7 Oliveira, G. P. et al. (2022). Ferramentas open-source de qualidade de dados para licitações públicas: Uma análise comparativa. In SBBD, pages 116–127. SBC.
8 Paula, E. L. et al. (2016). Deep learning anomaly detection as support fraud investigation in brazilian exports and anti-money laundering. In ICMLA, pages 954–960. IEEE.
9 Silva, M. O. et al. (2022). LiPSet: Um conjunto de Dados com Documentos Rotulados de Licitações Publicas. In SBBD DSW, pages 13–24. SBC.
10 Velasco, R. B. et al. (2021). A decision support system for fraud detection in public procurement. International Transactions in Operational Research, 28(1):27–47.